Consideration of the influence of supports in modeling the electromagnetic fields of 25 kV traction networks under emergency conditions

Single-phase 25 kV traction networks of electrified alternating current(AC)railways create electromagnetic fields(EMFs)with significant levels of intensity.The most intense magnetic fields occur when short circuits exist between the contact wire and rails or ground.Despite the short duration of exposure,they can adversely affect electronic devices and induce significant voltages in adjacent power lines,which is dangerous for operating personnel.Although numerous investigations have focused on modeling the EMF of traction networks and power lines,the challenge of determining the three-dimensional electromagnetic fields near metal supports during the flow of a short-circuit current through them is yet to be resolved.In this case,the field has a complex spatial structure that significantly complicates the calculations of intensities.This study proposes a methodology,algorithms,software,and digital models for determining the EMF in the described emergency scenarios.During the modeling process,the objects being studied were represented by segments of thin wires to analyze the distribution of the electric charge and calculate the intensities of the electric and magnetic fields.This approach was implemented in the Fazonord software,and the modeling results show a substantial increase in EMF levels close to the support,with a noticeable decrease in the levels as the distance from it increases.The procedure implemented in the commercial software Fazonord is universal and can be used to determine electromagnetic fields at any electrical power facility that includes live parts of limited length.Based on the proposed procedure,the EMF near the supports of overhead power lines and traction networks of various designs could be determined,the EMF levels at substations can be calculated,and the influence of metal structures located near traction networks,such as pedestrian crossings at railway stations,can be considered.

Analysis of the Role of Problem-Based Independent Learning Model in Teaching Cerebral Ischemic Stroke First Aid in Emergency Medicine

Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our hospital from May 2022 to May 2023 were selected for the study.They were divided into Group A(45,conventional teaching method)and Group B(45 cases,PBL independent learning model)by randomized numerical table method to compare the effects of the two groups.Results:The teaching effect indicators and student satisfaction scores in Group B were higher than those in Group A(P<0.05).Conclusion:The use of the PBL independent learning model in the teaching of CIS first aid can significantly improve the teaching effect and student satisfaction.

Simulation based on a modified social force model for sensitivity to emergency signs in subway station

The subway is the primary travel tool for urban residents in China. Due to the complex structure of the subway and high personnel density in rush hours, subway evacuation capacity is critical. The subway evacuation model is explored in this work by combining the improved social force model with the view radius using the Vicsek model. The pedestrians are divided into two categories based on different force models. The first category is sensitive pedestrians who have normal responses to emergency signs. The second category is insensitive pedestrians. By simulating different proportions of the insensitive pedestrians, we find that the escape time is directly proportional to the number of insensitive pedestrians and inversely proportional to the view radius. However, when the view radius is large enough, the escape time does not change significantly, and the evacuation of people in a small view radius environment tends to be integrated. With the improvement of view radius conditions, the escape time changes more obviously with the proportion of insensitive pedestrians. A new emergency sign layout is proposed, and the simulations show that the proposed layout can effectively reduce the escape time in a small view radius environment. However, the evacuation effect of the new escape sign layout on the large view radius environment is not apparent. In this case, the exit setting emerges as an additional factor affecting the escape time.

Resilience assessment and optimization method of city road network in the post-earthquake emergency period

The post-earthquake emergency period,which is a sensitive time segment just after an event,mainly focuses on saving life and restoring social order.To improve the seismic resilience of city road networks,a resilience evaluation method used in the post-earthquake emergency period is proposed.The road seismic damage index of a city road network can consider the influence of roads,bridges and buildings along the roads,etc.on road capacity after an earthquake.A function index for a city road network is developed,which reflects the connectivity,redundancy,traffic demand and traffic function of the network.An optimization model for improving the road repair order in the post-earthquake emergency period is also developed according to the resilience evaluation,to enable decision support for city emergency management and achieve the best seismic resilience of the city road network.The optimization model is applied to a city road network and the results illustrate the feasibility of the resilience evaluation and optimization method for a city road network in the post-earthquake emergency period.

Short-term effects of low-level PM_(2.5),PM_(10),O_(3),and tropical meteorological conditions on emergency department visits for respiratory diseases in Haikou,China

Objective:To assess the correlation between atmospheric pollutants,meteorological factors,and emergency department visits for respiratory diseases in Haikou City.Methods:Daily data on atmospheric pollutants,meteorological factors,and emergency department visits for respiratory diseases in Haikou City from 2018 to 2021 were collected.The Spearman rank correlation test was used to analyze the correlation,and a distributed lag non-linear model was employed to analyze the health effects and lag impacts of environmental factors.Subgroup analyses were conducted based on sex and age.Results:According to the criteria of International Classification of Diseases(ICD-10:J00-J99),a total of 221913 cases were included,accounting for 21.3%of the total emergency department visits in Haikou City.For every 1℃increase in temperature,the risk of emergency department visits increased by 1.029%(95%CI 1.016%-1.042%).Relative humidity greater than 80%reduced the risk of visits,while higher atmospheric pressure(>1010 hpa)also decreased the likelihood of daily emergency department visits.Higher concentrations of PM_(2.5)(30-50μg/m^(3)),PM10(>60μg/m^(3)),and O_(3)(75-125μg/m^(3))were associated with increased visits.Higher temperatures(>25℃)have a greater impact on females and children aged 0-14 years,while males are more sensitive to low atmospheric pressure.Individuals aged 65 and above exhibited increased sensitivity to O_(3)concentration,and the effects of PM2.5,PM10,and O_(3)are more pronounced in individuals over 14 years old.Conclusions:Short-term exposure to high temperatures,particulate matter pollutants(PM_(2.5)and PM_(10)),and ozone(O_(3))is associated with increased emergency department visits for respiratory diseases.

Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration

The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.

Comparison of emergency surgical cricothyroidotomy and percutaneous cricothyroidotomy by experienced airway providers in an obese,in vivo porcine hemorrhage airway model

Background: Emergency front-of-neck airway(eFONA) is a life-saving procedure in “cannot intubate, cannot oxygenate”(CICO). The fastest and most reliable method of eFONA has not been determined. We compared two of the most advocated approaches: surgical cricothyroidotomy and percutaneous cricothyroidotomy, in an obese, in vivo porcine hemorrhage model, designed to introduce real-time physiological feedback, relevant and high provider stress. The primary aim was to determine the fastest method to secure airway. Secondary aims were arterial saturation and partial pressure of oxygen, proxy survival and influence of experience.Methods: Twelve pigs [(60.3±4.1) kg] were anesthetized and exposed to 25%–35% total blood volume hemorrhage before extubation and randomization to Seldinger technique “percutaneous cricothyroidotomy”(n=6) or scalpelbougie-tube technique “surgical cricothyroidotomy”(n=6). Specialists in anesthesia and intensive care in a tertiary referral hospital performed the eFONA, simulating an actual CICO-situation.Results: In surgical cricothyroidotomy vs. percutaneous cricothyroidotomy, the median(interquartile range, IQR) times to secure airway were 109(IQR 71–130) s and 298(IQR 128–360) s(P=0.0152), arterial blood saturation(SaO2) were 74.7(IQR 46.6–84.2)% and 7.9(IQR 4.1–15.6)%(P=0.0167), PaO_(2) were 7.0(IQR 4.7–7.7) kPa and 2.0(IQR 1.1–2.9) kPa(P=0.0667), and times of cardiac arrest(proxy survival) were 137–233 s, 190(IQR 143–229) s, from CICO. All six animals survived surgical cricothyroidotomy, and two of six(33%) animals survived percutaneous cricothyroidotomy. Years in anesthesia, 13.5(IQR 7.5–21.3), did not influence time to secure airway.Conclusions: eFONA by surgical cricothyroidotomy was faster and had increased oxygenation and survival, when performed under stress by board certified anesthesiologists, and may be an indication of preferred method in situations with hemorrhage and CICO, in obese patients.

Location of emergency rescue center based on SIR epidemiological model

In view of the pressure time of emergency rescue against the infectious diseases,a mathematical model to optimize the location of emergency rescue centers is proposed.The model takes full account of the spread function of infectious diseases,the cycle of pulse vaccination,the distance between the demand area and the emergency rescue centers,as well as the building and maintenance cost for the emergency rescue center,and so on.At the same time,the model integrates the traditional location selection models which are the biggest cover model,the p-center model and the p-median model,and it embodies the principles of fairness and efficiency for the emergency center location.Finally,a computation of an example arising from practice provides satisfactory results.

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing:A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs)such as schools,colleges,hospitals,and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs)for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step,flood susceptibility maps were developed using machine learning models(MLMs),including:Levenberg-Marquardt back propagation(LM-BP)neural network and decision trees(DT)and multi-criteria decision making(MCDM)method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC)curve.Mathematical approaches in a geographic information system(GIS)for four well-known LAM problems affecting emergency rescue time are proposed:maximal covering location problem(MCLP),the maximize attendance(MA),p-median problem(PMP),and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed,and that some areas were not adequately served by EECs(i.e.,not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs,and that application of the models could contribute to reducing human casualties,property losses,and improve emergency operation.

Emergency Tasks Planning Based on Formal Modeling of Emergency Plan and HTN Planning System SHOP2

A theoretical approach of ordered emergency tasks generation is proposed for dealing with a specific emergency event rapidly, exactly and effectively. According to the general principles of an emergency plan developed to response to an emergency management, a workflow model is employed to complete the formal modeling of concrete emergency plan firstly. Then the HTN planning system SHOP2 is introduced, the transformation method of domain knowledge from emergency domain to SHOP2 domain is studied. At last, the general procedure to solve the emergency decision prob-lems and to generate executive emergency tasks is set up drawing support from SHOP2 planning system, which will combine the principles (or knowledge) of emergency plan and the real emergency situations.

A numerical method for the simulation of freight train emergency braking operations based on the UIC braked weight percentage

The present paper shows the development of a strategy for the calculation of the air brake forces of European freight trains. The model is built to upgrade the existing Politecnico di Torino longitudinal train dynamics(LTD) code LTDPoliTo, which was originally unable to account for air brake forces. The proposed model uses an empirical exponential function to calculate the air brake forces during the simulation, while the maximum normal force on the brake friction elements is calculated according to the indication of the vehicle braked weight percentage.Hence, the model does not require to simulate in detail the fluid dynamics in the brake pipe nor to precisely know the main parameters of the braking system mounted on each vehicle. The model parameters are tuned to minimize the difference between the braking distance computed by the LTDPoliTo code and the value prescribed by the UIC544-1 leaflet in emergency braking operations. Simulations are run for different configurations of freight train compositions including a variable number of Shimmns wagons trailed by an E402B locomotive at the head of the train, as suggested in a reference literature paper. The results of the proposed method are in good agreement with the target braking distances calculated according to the international rules.

Enhancing emerging technology discovery in nanomedicine by integrating innovative sentences using BERT and NLDA

Purpose:Nanomedicine has significant potential to revolutionize biomedicine and healthcare through innovations in diagnostics,therapeutics,and regenerative medicine.This study aims to develop a novel framework that integrates advanced natural language processing,noise-free topic modeling,and multidimensional bibliometrics to systematically identify emerging nanomedicine technology topics from scientific literature.Design/methodology/approach:The framework involves collecting full-text articles from PubMed Central and nanomedicine-related metrics from the Web of Science for the period 2013-2023.A fine-tuned BERT model is employed to extract key informative sentences.Noiseless Latent Dirichlet Allocation(NLDA)is applied to model interpretable topics from the cleaned corpus.Additionally,we develop and apply metrics for novelty,innovation,growth,impact,and intensity to quantify the emergence of novel technological topics.Findings:By applying this methodology to nanomedical publications,we identify an increasing emphasis on research aligned with global health priorities,particularly inflammation and biomaterial interactions in disease research.This methodology provides deeper insights through full-text analysis and leading to a more robust discovery of emerging technologies.Research limitations:One limitation of this study is its reliance on the existing scientific literature,which may introduce publication biases and language constraints.Additionally,manual annotation of the dataset,while thorough,is subject to subjectivity and can be time-consuming.Future research could address these limitations by incorporating more diverse data sources,and automating the annotation process.Practical implications:The methodology presented can be adapted to explore emerging technologies in other scientific domains.It allows for tailored assessment criteria based on specific contexts and objectives,enabling more precise analysis and decision-making in various fields.Originality/value:This study offers a comprehensive framework for identifying emerging technologies in nanomedicine,combining theoretical insights and practical applications.Its potential for adaptation across scientific disciplines enhances its value for future research and decision-making in technology discovery.

Simulation Modeling on Emergency Evacuation in High-Speed Railway Stations in China

A simulation study on occupant evacuation in high-speed railway stations （HSRSs） was presented in China. Pathfinder was employed as the simulation platform and a typical HSRS in a medinm-sized city in China was selected for model development. The model was carefully calibrated and validated by comparing simulation results with field data. Evacuation efficiency could be improved with the increased door width while such effect decreased when the door width reached a marginal value. And the marginal value varied under different occupant densities. An exponential function between evacuation lime and occupant density was fitted, indicating that occupant density significantly affected evacuation efficiency. A set of different evacuation strategies were compared, in terms of their evacuation performances. It was found that a balanced door usage would result in more efficient evacuations in HSRSs. Thus occupant flows were suggested to be managed considering door capacity. To avoid potential safety issues caused by such strategy （ e. g. , more occupants could be evacuated from a smaller area designed with higher door capacity ）, occupants needed to enhance their awareness of following evacuation guidance instead of panic escape in emergencies. Moreover, such safety issues could also be avoided during the design phase that the evacuation capacity was designed to be proportional to the room capacity for each floor. The results of this study provide valuable information for HSRS design and flow management in China.

A prediction model for large vessel occlusion in suspected stroke patients based on available prehospital information

Objective:Early and accurate identification of large vessel occlusion(LVO)acute ischemic stroke(AIS)patients is critically important for stroke management.Practicable scales with simple items can facilitate prehospital paramedics distinguishing LVO-AIS patients with high efficiency and help to avoid unnecessary and costly delays.The current study aims to develop a screening tool to predict AIS-LVO patients based on prehospital available data.Method:A total of 251 suspected stroke patients who were transported to the emergency department of our hospital via emergency medical services were consecutively enrolled from August,2020 to January,2022.Data including demographic information,medical history,clinical manifestations,and vital signs were collected.A multivariate logistic regression model was developed based on statistically significant variables selected from univariate analysis.Result:Forty-two patients(16.7%)were diagnosed as LVO-AIS based on imaging validation at admission.A comprehensive model was developed with past medical history factors such as atrial fibrillation and coronary heart disease,vital signs such as systolic blood pressure,and prominent symptoms and signs such as gaze palsy,facial paralysis,and dysarthria.The model showed better diagnostic performance in terms of area under the receiver operating characteristic curves(0.884,95%CI,0.830-0.939),which was higher than other common prehospital prediction scales such as the Face,Arm,Speech,Time test(FAST),the Field Assessment Stroke Triage for Emergency Destination(FAST-ED)scale,and the Gaze-Face-Arm-Speech-Time test(G-FAST).Calibration curve analysis,decision curve analysis,and clinical impact curve analysis further validated the reliability,net benefit,and potential clinical impact of the prediction model,respectively.Conclusion:We conducted a prediction model based on prehospital accessible factors including past history of atrial fibrillation and coronary heart disease,systolic blood pressure,and signs such as gaze palsy,facial palsy,and dysarthria.The prediction model showed good diagnostic power and accuracy for identification of the high-risk patients with LVO and may become an effective tool for the LVO recognition in prehospital settings.Future studies are warranted to refine and validate the model further in order to enhance the accuracy and objectivity of clinical judgments.

Multi-layer Evacuation Model: A solution of Emergency Evacuation

The large-scale population accumulation in modem cities has become one of their important characteristics. With the development of urbanization in the world, the large-scale gathering activities are increasing, and the accidents caused by them are also rising. At the same time, the evacuation of visitors is faced with severe challenges in the event of an emergency such as terrorist attacks. The main problem for tourists is how to evacuate quickly and safely in an emergency. The Louvre is one of the largest and most visited art museums in the world.Visitors are large and come from all over the world, the volume of passengers varies greatly, and the interior architecture design is complicated, etc. These characteristics challenge the design of evacuation paths. Based on the consideration of these factors, we should develop the optimal evacuation scheme and minimize the accident risk and evacuation cost.

Location Determination Of Optimal Emergency System For Hurricane Disaster Based On Mathematical Modeling

This article first introduces the current research status of space optical communication,and gives a brief overview of the development and application prospects of space optical communication,explaining its important research significance.Then,the working principle of ATP in space optical communication system is studied,the mathematical model of ATP control system is established according to the actual needs,and the ATP control system design of space optical communication is designed.By selecting appropriate motors and gyroscopes as the actuators and detection elements of the system,substituting the actual parameters for simulation analysis,and correcting and verifying the results,some useful results are obtained.The simulation results show the rationality and effectiveness of the ATP design scheme.

Influence range of emergency under special events based on CTM

To determine the dynamic influence range of emergencies under special events, the spacial and temporal characteristics of the traffic flow are studied by simulation based on the cell transmission model （CTM）. Based on the traffic management measures used under special events, a semi-dynamic assignment algorithm is proposed, which is combined with an algorithm for logit multi-path traffic assignment and the CTM. In a simple calculation network, the spacial and temporal characteristics of traffic flows which vary with different traffic management schemes are studied, and a method to obtain the influence range of emergency is proposed by computing the jam time of the intersections. By contrasting the average delay of each vehicle, the dissipation effect is studied under two different traffic management schemes. The example shows that the spatial and temporal variety of the traffic flow can be easily simulated and the influence range of emergency can be confirmed by the method based on the CTM. The proposed method provides a new idea for decision-making on traffic management under emergency under special events.

Collaborative planning approach for anti-bioterrorism emergency facility location based on aerodynamics

To smooth the correlation process from bio-virus diffusion to emergency relief response,the Gaussian plume model is used to describe the diffusion of dangerous sources,where the bio-virus concentration at any given point in affected areas can be calculated.And the toxic load rule is introduced to define the borderline of the dangerous area at different levels.Combined with this,different emergency levels of different demand points in dangerous areas are confirmed using fuzzy clustering,which allows demand points at the same emergency level to cluster in a group.Some effective emergency relief centers are chosen from the candidate hospitals which are located in different emergency level affected areas by set covering.Bioterrorism experiments which were conducted in Nanjing,Jiangsu province are simulated,and the results indicate that the novel method can be used efficiently by decision makers during an actual anti-bioterrorism relief.